Guangjie Han
Papers
7
Total Citations
72
H-Index
5
About
Guangjie Han is a leading researcher in intelligent robotics, underwater autonomous systems, and the Internet of Things (IoT), with a focus on enabling efficient, adaptive, and collaborative machine intelligence. His major contributions span multi-AUV reinforcement learning for underwater target tracking, where he pioneered hierarchical and interrupted software-defined approaches that dramatically improve coordination and time efficiency in dynamic marine environments. Han has also advanced trajectory prediction in heterogeneous traffic systems for the Internet of Vehicles, and developed dynamic collaborative charging algorithms to solve energy bottlenecks in Industrial IoT networks. His work on Drosophila-vision-inspired motion perception models bridges computational biology and robotics, while his research on multirobot collaborative SLAM using LiDAR remote sensing enhances geospatial data collection for urban planning. With over 19 citations on his most recent papers and a growing portfolio of high-impact publications, Han’s innovations are shaping next-generation autonomous systems. Notably, he has guest-edited special issues on smart agricultural applications, reflecting his commitment to translating robotic intelligence into real-world sustainability solutions.
Research Focus
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Top Papers
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